Chinese AI startup Moonshot AI has unveiled Kimi K2, a trillion-parameter open-source language model that outperforms GPT-4 in critical benchmarks, particularly in coding and autonomous agent tasks. The model’s standout feature is its optimization for “agentic” capabilities — the ability to autonomously use tools, write and execute code, and complete complex multi-step tasks without human intervention. In benchmark tests, Kimi K2 achieved 65.8% accuracy on SWE-bench Verified, a challenging software engineering benchmark, outperforming most open-source alternatives and matching some proprietary models. […] On LiveCodeBench, arguably the most realistic coding benchmark available, Kimi K2 achieved 53.7% accuracy, decisively beating DeepSeek-V3’s 46.9% and GPT-4.1’s 44.7%. More striking still: it scored 97.4% on MATH-500 compared to GPT-4.1’s 92.4%, suggesting Moonshot has cracked something fundamental about mathematical reasoning that has eluded larger, better-funded competitors.
But here’s what the benchmarks don’t capture: Moonshot is achieving these results with a model that costs a fraction of what incumbents spend on training and inference. While OpenAI burns through hundreds of millions on compute for incremental improvements, Moonshot appears to have found a more efficient path to the same destination. It’s a classic innovator’s dilemma playing out in real time — the scrappy outsider isn’t just matching the incumbent’s performance, they’re doing it better, faster, and cheaper.
Read more of this story at Slashdot.